Human movement has been a large window into the functioning of the nervous system. Behavioral scientists have had major accomplishments, such as documenting movement milestones in human development and establishing a relationship between brain and behavior in typical and atypical populations. These measurements are performed today with a cornucopia of sophisticated techniques, ranging from infrared and video to wireless sensor networks. However, despite the tremendous progress on measuring human movement, we still don't fully understand, for example, motor decline in elderly people or Parkinson's disease during daily living activities at home and the workplace;or how atypical social interaction in autism or developmental coordination disorder are manifested in body gestures. Why can't we yet deal with problems of such nature? It is clear that the problems mentioned above have characteristics that are beyond the state of the art or any single discipline. Thus, we propose a novel, interdisciplinary, and multi-level motion understanding tool to extract multi-scaled, nested representations of transitive and intransitive actions and communicative actions at different levels of abstraction at the "individual" and "workgroup" levels. Our specific aim is to develop a Human Action Language (HAL) tool, a tool for describing and understanding human actions. The underlying premise is that the space of human actions is characterized by a language;this new language has its own phonemes (primitives), its own morphemes (words/actions) and its own syntax, semantics and pragmatics. Although previous research has concentrated on finding primitives in very often isolated types of human action, the innovation here is the use of large amounts of human motion data in ecologically valid settings and in conjunction with modern data mining and grammatical induction techniques. To validate the HAL tool, we will apply it to assess atypical movement in Developmental Coordination Disorder (DCD) and Parkinson's disease (PD). Specifically, we propose to extract the DCD grammar and the PD grammar and compare them with the grammars from the control populations, investigating relationships between the corresponding grammars at the individual and workgroup levels. Our interdisciplinary team consists of a computational scientist, a behavioral scientist (motor development) , and a computational neuroscientist (motor control and learning). The proposed tool will extend the scope of behavioral sciences (grounding of language, imitation, and gesture-based social communication) and facilitate interdisciplinary research bringing together movement disorders specialists, behavioral scientists, physical or occupational therapists and computer scientists. Several NIH Institutes would benefit from the availability of such a tool, including NIA/NINDS, NIMH and NICHD. The ultimate goal is to better understand human action production and understanding, and to develop optimal diagnostic and intervention tools for populations with atypical movement patterns. The proposed tool will extend the scope of behavioral sciences (grounding of language, imitation, and gesture- based social communication) and facilitate interdisciplinary research bringing together movement disorders specialists, behavioral scientists, physical or occupational therapists and computer scientists. Several NIH Institutes would benefit from the availability of such a tool, including NIA/NINDS - for understanding motor decline in the elderly and neurological populations in single and group-based daily living activities, NIMH - for understanding stereotypical behaviors in populations affected with mental disorders, and NICHD - for understanding developmental aspects of cognitive motor behavior in children at school or home. The ultimate goal is to better understand human action production and understanding, and developing optimal diagnostic and intervention tools for populations with atypical movement patterns.